The topic of this paper is how to adjust the behavior of intelligent agents in the given environment. First, multi-agent systems are described, because they implement the described system. It describes what the agents are, their features and ways of action. Furthermore, more types of agents are defined, the ways they process information and act in the environment. Their function is defined through their ability to process information, for which purpose in this paper neural networks are used. Apart from the concept of neural networks, it is also introduced and explained the way in which agents can learn information, which will ultimately be the condition for the quality of behavior or the fulfillment of defined parameters. Since agents do not necessarily need to learn successful behavior, it is necessary to introduce something that improves their behavior. For this purpose, evolutionary algorithms are used, inspired by nature, and only those agents that meet the given conditions are chosen to create new ones, similar to them. The goal of the project is to create a program that implements the described, and show how the agents behave, that is, their ability to learn is observed.